Optimal sizing and technology selection of hybrid energy storage system with novel dispatching power for wind power integration

Wind power uncertainty is a problem in large-scale wind farms integration into the network. The use of energy storage systems (ESSs) is a practical solution for power dispatching of renewable energy sources (RESs). RESs need storage with high power and energy capacity, while none of ESSs has these features simultaneously. Utilizing the hybrid energy storage system (HESS) is the accepted solution. This paper introduces a power management method with comprehensive linearized model for HESS optimal sizing, technology selection and wind-HESS power dispatching. By utilizing the limited wind power and HESS, the problem of large storage rating in the existing wind power dispatching method is resolved. The input data is reduced using discrete wavelet transform and clustering method and the HESS optimal size and types are determined considering various types of ESSs with mixed-integer linear programming and maximizing the net present value. Additionally, the storage lifetime is maximized by considering its replacement cost. In short-term power management, the wind-HESS performance and delivery of prescheduled power to the network are investigated. Finally, the proposed method is evaluated by applying it to the real data of a wind farm scaled down to the 3 MW power level to be compared to other studies better.

Automated summary

This paper introduces a power management method utilizing a hybrid energy storage system to address the uncertainty of wind power integration into the grid. By using discrete wavelet transform and clustering methods, combined with mixed-integer linear programming and maximizing net present value, the optimal size and type of energy storage systems are determined. The effectiveness of the proposed method is verified through real data validation at a scaled-down wind farm.